Compatibility mix degree index: A novel measure to characterize urban land use mix pattern. (May 2019) - Zhuo, Yuefei; Zheng, Hongyu; Wu, Cifang; Xu, Zhongguo; Li, Guan; Yu, Zhenning
Abstract: The mixing of land uses lies at the core of understanding their characteristics in cities. Some existing land use mix measures have been used to quantify the mix degree from different perspectives. However, these existing indices mainly cover only two dimensions of the land use mix concept, namely, distance and quantity, and cannot effectively delineate the picture of land use mix. Thus, we propose a new quantification framework of land use mix by involving a third dimension, that is, the "attribute" level of the land use mix concept. On the basis of this framework, we develop a novel measure called (weighted) vector-based mix degree index (VMDI/WVMDI) to address the compatibility mix degree by incorporating the compatibility relations between different land uses. This novel measure adopts vector land use data and compatibility relations. To some extent, VMDI/WVMDI can overcome some of the deficiencies of existing land use mix measures. We select Guangzhou as a study area in evaluating the proposed measure. In addition, the "head/tail breaks" classification scheme is employed for results with heavy-tailed distribution. By using this scheme, we clearly identify several clustered regions of land use mix in Guangzhou, which might be useful for urban planners and policy makers. Compared with some traditional measures, VMDI/WVMDI can be more efficient in depicting the compatibility relation between land use parcels. Highlights: A more effective quantification framework of land use mix is proposed. A novel measure is developed to address the compatibility mix degree among different land uses. The "Head/tail breaks" classification scheme is adopted to reveal the underlying scaling pattern of outcomes in Guangzhou. By comparing with previous measures, this measure shows some superior at the quantification of compatibility relations.